Accelerometer & gyro accuracy in different mobile device

Question

I want to implement an indoor localisation system using the sensors of a mobile device (accelerometer, compass, gyro) . This problem was already discussed here on several pl

Answer 1

Here are a few general notes to consider: The issue of time syncing sensor measurements is managed by Kalman filters very well. The KF is very powerful but will take some time to learn and implement. It's a very big leap.

With KF you can do data fusion of many types of sensors (rate gyros, accelerometers, and angle or position measurements of all types) at varying data rates.

The overall method is called Data Fusion. If the item you are tracking is moving, then the process is referred to as 'trajectory estimation'. The KF algorithm estimates the object's position, velocity, and acceleration over time, based on the all measurements and certain assumptions about the object's ability to move (the dynamic model).

For example, if the object is a cow, you can make certain assumptions about the speed, acceleration, and position (it will be on the earth's surface). If the object is a rocket, the assumptions about the possible movements will be different. Knowing the object's 'dynamic model' increases the accuracy of the trajectory estimation.

Another nice thing about the KF algorithm is it helps filter out sensor noise based on a 'noise model' and a sensor accuracy model. You can also model sensor biases, drifts, etc.